Improved Bacterial Foraging Optimization Algorithm with Information Communication Mechanism for Nurse Scheduling
As a NP-hard combinatorial problem, nurse scheduling problem (NSP) is a well-known personnel scheduling task whose goal is to create a nurse schedule under a series of hard and soft constraints in a practical world. In this paper, a variant of structure-redesigned-based bacterial foraging optimization (SRBFO) with a dynamic topology structure (SRBFO-DN) is employed for solving nurse scheduling problem (NSP). In SRBFO-DN, each bacterium achieves cooperation by information exchange mechanism switching the topology structure between star topology and ring topology. A special encoding operation of bacteria in SRBFO-DN is adopted to transform position vectors into feasible solutions, which can make SRBFO-DN successfully dealing with this typical difficult and discrete NSP. Experiment results obtained by SRBFO-DN compared with SRBFO and SPSO demonstrated that the efficiency of the proposed SRBFO-DN algorithm is better than other two algorithms for dealing with NSP.
KeywordsBacterial foraging optimization Topology structure Nurse scheduling problem
This work is partially supported by The National Natural Science Foundation of China (Grants nos. 71001072, 71271140, 71471158, 71461027, 61262071), the Natural Science Foundation of Guangdong Province (Grant nos. S2012010008668, 9451806001002294), Shenzhen Science and Technology Plan Project (Grant no. CXZZ20140418182638764).
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